Robust design modeling with correlated quality characteristics using a multicriteria decision framework

Srikrishna Madhumohan Govindaluri*, Byung Rae Cho

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةReview articleمراجعة النظراء

46 اقتباسات (Scopus)


Robust design (RD) is a popular design methodology for minimizing the variability of product performance, thereby, improving the quality of a product. Although RD principles have been widely implemented in many industries, and a number of new RD models have been reported in the literature, there is ample room for improvement. First, a number of RD models consider a single quality characteristic (QC). In reality, however, the judgmental basis of a product from the perspective of the customer is characterized by the assessment of multiple QCs, which are often correlated. Second, previous models often fail to emphasize customer preferences in the modeling and optimization phases. To rectify these shortcomings, this paper proposes a compromise programming model for synthesizing Pareto solutions that represent compromised trade-offs between multiple correlated QCs based on the customer's preferences. The Tchebycheff-metric-based compromise programming method employed to determine Pareto solutions is superior to the simplistic weighted sum and goal programming approaches that may fail to explore the full set of Pareto points for a multi-objective optimization problem.

اللغة الأصليةEnglish
الصفحات (من إلى)423-433
عدد الصفحات11
دوريةInternational Journal of Advanced Manufacturing Technology
مستوى الصوت32
رقم الإصدار5-6
المعرِّفات الرقمية للأشياء
حالة النشرPublished - مارس 2007
منشور خارجيًانعم

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